Spartina alterniflora identification and early warning method

Abstract

The invention relates to identification, monitoring and early warning of scattered plaque spartina alterniflora in four seasons of the year, in particular to a spartina alterniflora identification and early warning method, which comprises the following steps of: 1, building an acquisition platform, and acquiring a spartina alterniflora image; 2, splicing and segmenting the image; 3, making a training set, a verification set and a test set; and 4, selecting a mainstream convolutional neural network, and training, verifying and testing the model. 5, judging the recognition accuracy, and selecting the convolutional neural network meeting the conditions; 6, data of the four periods are trained respectively, and spatial distribution of the spartina alterniflora is carried out; 7, constructing a hazard grade evaluation model; 8, obtaining the diffusion distance of the spartina alterniflora; 9, acquiring biomass crop parameters of the spartina alterniflora; and 10, generating a spartina alterniflora early warning visual heat map. According to the method, accurate identification of the spartina alterniflora under the local scale is realized, the early warning visual heat map is generated, and data information is provided for early monitoring and prevention of the spartina alterniflora.

Description

technical field [0001] The invention relates to a method for identifying and early warning of Spartina alterniflora. Background technique [0002] Spartina alterniflora is produced in North America and has the advantages of fighting against wind and sand and protecting river banks. For the purpose of protecting beaches and shores, my country introduced the seedlings and seeds of Spartina alterniflora from the United States in 1979, and carried out trial planting experiments in Luoyuan Bay, Fujian Province, and then began to promote trial planting in coastal areas of my country. Spartina alterniflora expands its population through sexual and asexual reproduction. After years of proliferation, it has been widely distributed in the intertidal zone of China's coast, which has a serious impact on the structure and function of China's coastal wetland ecosystem. Due to the low resolution of current satellite remote sensing, it is difficult to monitor the scattered patches of Spart...

AI Technical Summary

Problems solved by technology

[0003] In order to solve the problem of monitoring and early warning of scattered patches of Spartina alterniflora, the present invention proposes a recognition and early warning method for Spartina alterniflora based on UAV remote sensing and deep learning neural network

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